Triple

T11624929
Position Surface form Disambiguated ID Type / Status
Subject Michel Monet E276239 entity
Predicate mother P120 FINISHED
Object Camille Doncieux E45129 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Camille Doncieux | Statement: [Michel Monet, mother, Camille Doncieux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Camille Doncieux
Context triple: [Michel Monet, mother, Camille Doncieux]
  • A. Camille Doncieux chosen
    Camille Doncieux was the first wife and frequent model of French Impressionist painter Claude Monet, known for appearing in many of his early masterpieces.
  • B. Annick Castiaux
    Annick Castiaux is a Belgian academic and university leader who serves as rector of the University of Namur.
  • C. Catherine Lalumière
    Catherine Lalumière is a French politician and lawyer known for her prominent role in European institutions and advocacy for European integration and human rights.
  • D. Danielle Breton
    Danielle Breton is a central character in Brian De Palma’s psychological horror-thriller film "Sisters," known for her disturbing and complex dual identity.
  • E. Catherine Lemaire
    Catherine Lemaire was the wife of French Realist painter Jean-François Millet and the mother of his children, who supported him during his career in 19th-century France.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a12416908190ac2dcd7f7ebb308f completed April 10, 2026, 7:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee87745b388190a78958fa0c08b89b completed April 26, 2026, 9:45 p.m.
Created at: April 8, 2026, 9:39 p.m.